Distr-LapRLS MATLAB code
Description
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This is a serial implementation in MATLAB of the algorithm presented in:
Fierimonte R., Scardapane S., Uncini A. and M. Panella - Fully
Decentralized Semi-supervised Learning via Privacy-Preserving
Matrix Completion.
The paper describing the code is currently under review at IEEE Transactions
on Neural Networks and Learning Systems.
The proposed algorithm extends the LapRLS algorithm to distributed learning
where the training set is distrubuted through a network of agents, each of
those has access only to few patterns. The Laplacian matrix used to store
information about the patterns' similarity is computed using a novel
distributed Euclidan Distance Matrix (EDM) completion algorithm.
Documentation
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A demo file to perform simulations is provided. All the code is commented
with appropriate instructions and references where needed.
Contacts
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If you have any request, bug report, or inquiry, you can contact
the author at roberto [dot] fierimonte [at] gmail [dot] com.